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AAPG Bulletin

Abstract

AAPG Bulletin, V. 104, No. 5 (May 2020), P. 1167-1196.

Copyright ©2020. The American Association of Petroleum Geologists. All rights reserved.

DOI: 10.1306/12031919080

Fluvial architecture and four-dimensional saturation Previous HitmodelingTop of a steam flood: Kern River field, California

D. K. Larue,1 J. P. Allen,2 and D. Beeson3

1Chevron North America Exploration and Production, San Joaquin Valley Business Unit, Bakersfield, California; [email protected]
2Chevron North America Exploration and Production, San Joaquin Valley Business Unit, Bakersfield, California; [email protected]
3Chevron North America Exploration and Production, San Joaquin Valley Business Unit, Bakersfield, California; [email protected]

ABSTRACT

The upper Miocene Kern River Formation at Kern River field is a thick succession of braided stream deposits. Because the oil field has been penetrated by more than 21,000 wells, with well spacing typically of 2.5 ac (104 m2), high-quality imaging of the reservoir can be accomplished using well logs. The field contains more than 650 observation wells recording temperatures and saturation, such that heating and drainage of the reservoir can be characterized over time. Oil and gas saturations in a 360-ac (1.5 × 106-m2) study area within the Kern River field were modeled in three dimensions over time, creating a four-dimensional (4-D) earth model. Static lithology and porosity properties were first created. Then, temperature, oil, and gas saturations were kriged using data from observation wells at different time increments. From these kriged models, difference models were created to show changes in oil and gas saturation with time. Changes in oil volumes in the 4-D model matched produced volumes within a 10% error. Next, categorical descriptions of net oil saturation were made (best oil, background oil, partially drained, and residual saturations), and temporal evolution of the volumes of the different categories was modeled. By characterizing the reservoir in detail using the well-log data to define a reservoir framework and the observation wells to characterize changes over time, significant challenges in steam-flood reservoir management can be addressed, including determining which parts of the reservoir are producing the most and recognizing parts of the reservoir that are not actively draining.

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